{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<table class=\"ee-notebook-buttons\" align=\"left\">\n",
        "    <td><a target=\"_blank\"  href=\"https://github.com/giswqs/earthengine-py-notebooks/tree/master/Datasets/Vectors/us_census_datasets.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/Datasets/Vectors/us_census_datasets.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/Datasets/Vectors/us_census_datasets.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Install Earth Engine API and geemap\n",
        "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://geemap.org). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n",
        "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Installs geemap package\n",
        "import subprocess\n",
        "\n",
        "try:\n",
        "    import geemap\n",
        "except ImportError:\n",
        "    print('Installing geemap ...')\n",
        "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "import ee\n",
        "import geemap"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Create an interactive map \n",
        "The default basemap is `Google Maps`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/basemaps.py) can be added using the `Map.add_basemap()` function. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map = geemap.Map(center=[40,-100], zoom=4)\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Add Earth Engine Python script "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Add Earth Engine dataset\n",
        "dataset = ee.FeatureCollection('TIGER/2010/Blocks')\n",
        "visParams = {\n",
        "  'min': 0.0,\n",
        "  'max': 700.0,\n",
        "  'palette': ['black', 'brown', 'yellow', 'orange', 'red']\n",
        "}\n",
        "\n",
        "# Turn the strings into numbers\n",
        "dataset = dataset.map(lambda f: f.set('pop10', ee.Number.parse(f.get('pop10'))))\n",
        "\n",
        "image = ee.Image().float().paint(dataset, 'pop10')\n",
        "\n",
        "Map.setCenter(-73.99172, 40.74101, 13)\n",
        "Map.addLayer(image, visParams, 'TIGER/2010/Blocks')\n",
        "# Map.addLayer(dataset, {}, 'for Inspector', False)\n",
        "\n",
        "\n",
        "dataset = ee.FeatureCollection('TIGER/2010/Tracts_DP1')\n",
        "visParams = {\n",
        "  'min': 0,\n",
        "  'max': 4000,\n",
        "  'opacity': 0.8,\n",
        "}\n",
        "\n",
        "# Turn the strings into numbers\n",
        "dataset = dataset.map(lambda f: f.set('shape_area', ee.Number.parse(f.get('dp0010001'))))\n",
        "\n",
        "# Map.setCenter(-103.882, 43.036, 8)\n",
        "image = ee.Image().float().paint(dataset, 'dp0010001')\n",
        "\n",
        "Map.addLayer(image, visParams, 'TIGER/2010/Tracts_DP1')\n",
        "# Map.addLayer(dataset, {}, 'for Inspector', False)\n",
        "\n",
        "\n",
        "dataset = ee.FeatureCollection('TIGER/2010/ZCTA5')\n",
        "visParams = {\n",
        "  'palette': ['black', 'purple', 'blue', 'green', 'yellow', 'orange', 'red'],\n",
        "  'min': 500000,\n",
        "  'max': 1000000000,\n",
        "}\n",
        "\n",
        "zctaOutlines = ee.Image().float().paint(**{\n",
        "  'featureCollection': dataset,\n",
        "  'color': 'black',\n",
        "  'width': 1\n",
        "})\n",
        "\n",
        "image = ee.Image().float().paint(dataset, 'ALAND10')\n",
        "# Map.setCenter(-93.8008, 40.7177, 6)\n",
        "Map.addLayer(image, visParams, 'TIGER/2010/ZCTA5')\n",
        "Map.addLayer(zctaOutlines, {}, 'borders')\n",
        "# Map.addLayer(dataset, {}, 'for Inspector', False)\n",
        "\n",
        "\n",
        "dataset = ee.FeatureCollection('TIGER/2016/Roads')\n",
        "roads = dataset.style(**{'color': '#4285F4', 'width': 1})\n",
        "Map.setCenter(-73.99172, 40.74101, 12)\n",
        "Map.addLayer(roads, {}, 'TIGER/2016/Roads')\n",
        "\n",
        "\n",
        "dataset = ee.FeatureCollection('TIGER/2018/Counties')\n",
        "visParams = {\n",
        "  'palette': ['purple', 'blue', 'green', 'yellow', 'orange', 'red'],\n",
        "  'min': 0,\n",
        "  'max': 50,\n",
        "  'opacity': 0.8,\n",
        "}\n",
        "\n",
        "# Turn the strings into numbers\n",
        "dataset = dataset.map(lambda f: f.set('STATEFP', ee.Number.parse(f.get('STATEFP'))))\n",
        "\n",
        "image = ee.Image().float().paint(dataset, 'STATEFP')\n",
        "countyOutlines = ee.Image().float().paint(**{\n",
        "  'featureCollection': dataset,\n",
        "  'color': 'black',\n",
        "  'width': 1\n",
        "})\n",
        "\n",
        "# Map.setCenter(-99.844, 37.649, 5)\n",
        "Map.addLayer(image, visParams, 'TIGER/2018/Counties')\n",
        "Map.addLayer(countyOutlines, {}, 'county outlines')\n",
        "# Map.addLayer(dataset, {}, 'for Inspector', False)\n",
        "\n",
        "\n",
        "dataset = ee.FeatureCollection('TIGER/2018/States')\n",
        "visParams = {\n",
        "  'palette': ['purple', 'blue', 'green', 'yellow', 'orange', 'red'],\n",
        "  'min': 500000000.0,\n",
        "  'max': 5e+11,\n",
        "  'opacity': 0.8,\n",
        "}\n",
        "image = ee.Image().float().paint(dataset, 'ALAND')\n",
        "# Map.setCenter(-99.844, 37.649, 5)\n",
        "Map.addLayer(image, visParams, 'TIGER/2018/States')\n",
        "# Map.addLayer(dataset, {}, 'for Inspector', False)\n"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Display Earth Engine data layers "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    }
  ],
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      "display_name": "Python 3",
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      "codemirror_mode": {
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